ITK
5.0.0
Insight Segmentation and Registration Toolkit
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#include <itkGradientDescentLineSearchOptimizerv4.h>
Gradient descent optimizer with a golden section line search.
GradientDescentLineSearchOptimizer implements a simple gradient descent optimizer that is followed by a line search to find the best value for the learning rate. At each iteration the current position is updated according to
Options are identical to the superclass's except for:
options Epsilon, LowerLimit and UpperLimit that will guide a golden section line search to find the optimal gradient update within the range :
[ learningRate * LowerLimit , learningRate * UpperLimit ]
where Epsilon sets the resolution of the search. Smaller values lead to additional computation time but better localization of the minimum.
By default, this optimizer will return the best value and associated parameters that were calculated during the optimization. See SetReturnBestParametersAndValue().
Definition at line 59 of file itkGradientDescentLineSearchOptimizerv4.h.
Public Member Functions | |
virtual ::itk::LightObject::Pointer | CreateAnother () const |
virtual const char * | GetNameOfClass () const |
virtual void | SetEpsilon (TInternalComputationValueType _arg) |
virtual TInternalComputationValueType | GetEpsilon () |
virtual void | SetLowerLimit (TInternalComputationValueType _arg) |
virtual TInternalComputationValueType | GetLowerLimit () |
virtual void | SetUpperLimit (TInternalComputationValueType _arg) |
virtual TInternalComputationValueType | GetUpperLimit () |
virtual void | SetMaximumLineSearchIterations (unsigned int _arg) |
virtual unsigned int | GetMaximumLineSearchIterations () |
Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType > | |
virtual ::itk::LightObject::Pointer | CreateAnother () const |
virtual void | EstimateLearningRate () |
virtual const TInternalComputationValueType & | GetConvergenceValue () const |
void | ResumeOptimization () override |
virtual void | SetConvergenceWindowSize (SizeValueType _arg) |
virtual void | SetMinimumConvergenceValue (TInternalComputationValueType _arg) |
void | StartOptimization (bool doOnlyInitialization=false) override |
void | StopOptimization () override |
virtual void | SetLearningRate (TInternalComputationValueType _arg) |
virtual const TInternalComputationValueType & | GetLearningRate () const |
virtual void | SetMaximumStepSizeInPhysicalUnits (TInternalComputationValueType _arg) |
virtual const TInternalComputationValueType & | GetMaximumStepSizeInPhysicalUnits () const |
virtual void | SetDoEstimateLearningRateAtEachIteration (bool _arg) |
virtual const bool & | GetDoEstimateLearningRateAtEachIteration () const |
virtual void | DoEstimateLearningRateAtEachIterationOn () |
virtual void | DoEstimateLearningRateAtEachIterationOff () |
virtual void | SetDoEstimateLearningRateOnce (bool _arg) |
virtual const bool & | GetDoEstimateLearningRateOnce () const |
virtual void | DoEstimateLearningRateOnceOn () |
virtual void | DoEstimateLearningRateOnceOff () |
virtual void | SetReturnBestParametersAndValue (bool _arg) |
virtual const bool & | GetReturnBestParametersAndValue () const |
virtual void | ReturnBestParametersAndValueOn () |
virtual void | ReturnBestParametersAndValueOff () |
Public Member Functions inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType > | |
SizeValueType | GetCurrentIteration () const override |
virtual const DerivativeType & | GetGradient () const |
SizeValueType | GetNumberOfIterations () const override |
virtual const StopConditionType & | GetStopCondition () const |
const StopConditionReturnStringType | GetStopConditionDescription () const override |
void | SetNumberOfIterations (const SizeValueType numberOfIterations) override |
virtual void | ModifyGradientByScales () |
virtual void | ModifyGradientByLearningRate () |
Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType > | |
virtual const MeasureType & | GetCurrentMetricValue () const |
virtual const ParametersType & | GetCurrentPosition () const |
virtual const ThreadIdType & | GetNumberOfWorkUnits () const |
virtual const ScalesType & | GetScales () const |
virtual const bool & | GetScalesAreIdentity () const |
bool | GetScalesInitialized () const |
virtual const MeasureType & | GetValue () const |
virtual const ScalesType & | GetWeights () const |
virtual const bool & | GetWeightsAreIdentity () const |
virtual void | SetNumberOfWorkUnits (ThreadIdType number) |
virtual void | SetScalesEstimator (ScalesEstimatorType *_arg) |
virtual void | SetWeights (ScalesType _arg) |
virtual void | SetMetric (MetricType *_arg) |
virtual MetricType * | GetModifiableMetric () |
virtual const MetricType * | GetMetric () const |
virtual void | SetScales (const ScalesType &scales) |
virtual void | SetDoEstimateScales (bool _arg) |
virtual const bool & | GetDoEstimateScales () const |
virtual void | DoEstimateScalesOn () |
virtual void | DoEstimateScalesOff () |
Public Member Functions inherited from itk::Object | |
unsigned long | AddObserver (const EventObject &event, Command *) |
unsigned long | AddObserver (const EventObject &event, Command *) const |
virtual void | DebugOff () const |
virtual void | DebugOn () const |
Command * | GetCommand (unsigned long tag) |
bool | GetDebug () const |
MetaDataDictionary & | GetMetaDataDictionary () |
const MetaDataDictionary & | GetMetaDataDictionary () const |
virtual ModifiedTimeType | GetMTime () const |
virtual const TimeStamp & | GetTimeStamp () const |
bool | HasObserver (const EventObject &event) const |
void | InvokeEvent (const EventObject &) |
void | InvokeEvent (const EventObject &) const |
virtual void | Modified () const |
void | Register () const override |
void | RemoveAllObservers () |
void | RemoveObserver (unsigned long tag) |
void | SetDebug (bool debugFlag) const |
void | SetReferenceCount (int) override |
void | UnRegister () const noexceptoverride |
void | SetMetaDataDictionary (const MetaDataDictionary &rhs) |
void | SetMetaDataDictionary (MetaDataDictionary &&rrhs) |
virtual void | SetObjectName (std::string _arg) |
virtual const std::string & | GetObjectName () const |
Public Member Functions inherited from itk::LightObject | |
virtual void | Delete () |
virtual int | GetReferenceCount () const |
itkCloneMacro (Self) | |
void | Print (std::ostream &os, Indent indent=0) const |
Static Public Member Functions | |
static Pointer | New () |
Static Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType > | |
static Pointer | New () |
Static Public Member Functions inherited from itk::Object | |
static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool flag) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
static Pointer | New () |
Protected Member Functions | |
void | AdvanceOneStep () override |
TInternalComputationValueType | GoldenSectionSearch (TInternalComputationValueType a, TInternalComputationValueType b, TInternalComputationValueType c, TInternalComputationValueType metricb=NumericTraits< TInternalComputationValueType >::max()) |
GradientDescentLineSearchOptimizerv4Template () | |
void | PrintSelf (std::ostream &os, Indent indent) const override |
~GradientDescentLineSearchOptimizerv4Template () override=default | |
Protected Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType > | |
GradientDescentOptimizerv4Template () | |
void | ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override |
void | ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) override |
void | PrintSelf (std::ostream &os, Indent indent) const override |
~GradientDescentOptimizerv4Template () override=default | |
Protected Member Functions inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType > | |
GradientDescentOptimizerBasev4Template () | |
~GradientDescentOptimizerBasev4Template () override=default | |
Protected Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType > | |
void | PrintSelf (std::ostream &os, Indent indent) const override |
ObjectToObjectOptimizerBaseTemplate () | |
~ObjectToObjectOptimizerBaseTemplate () override | |
Protected Member Functions inherited from itk::Object | |
Object () | |
bool | PrintObservers (std::ostream &os, Indent indent) const |
virtual void | SetTimeStamp (const TimeStamp &time) |
~Object () override | |
Protected Member Functions inherited from itk::LightObject | |
virtual LightObject::Pointer | InternalClone () const |
LightObject () | |
virtual void | PrintHeader (std::ostream &os, Indent indent) const |
virtual void | PrintTrailer (std::ostream &os, Indent indent) const |
virtual | ~LightObject () |
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::ConstPointer = SmartPointer< const Self > |
Definition at line 69 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::ConvergenceMonitoringType = itk::Function::WindowConvergenceMonitoringFunction<TInternalComputationValueType> |
Type for the convergence checker
Definition at line 88 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::DerivativeType = typename Superclass::DerivativeType |
Derivative type
Definition at line 81 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::InternalComputationValueType = TInternalComputationValueType |
It should be possible to derive the internal computation type from the class object.
Definition at line 78 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::MeasureType = typename Superclass::MeasureType |
Metric type over which this class is templated
Definition at line 84 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::ParametersType = typename Superclass::ParametersType |
Definition at line 85 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::Pointer = SmartPointer< Self > |
Definition at line 68 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::Self = GradientDescentLineSearchOptimizerv4Template |
Standard class type aliases.
Definition at line 66 of file itkGradientDescentLineSearchOptimizerv4.h.
using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::Superclass = GradientDescentOptimizerv4Template<TInternalComputationValueType> |
Definition at line 67 of file itkGradientDescentLineSearchOptimizerv4.h.
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Default constructor
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overrideprotecteddefault |
Destructor
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Advance one Step following the gradient direction. Includes transform update.
Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.
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Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.
Reimplemented from itk::Object.
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The epsilon determines the accuracy of the line search i.e. the energy alteration that is considered convergent.
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The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.
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The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.
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Run-time type information (and related methods).
Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.
Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4Template< TInternalComputationValueType >.
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The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.
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New macro for creation of through a Smart Pointer
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Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.
Reimplemented from itk::Object.
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The epsilon determines the accuracy of the line search i.e. the energy alteration that is considered convergent.
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The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.
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The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.
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The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.
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Definition at line 136 of file itkGradientDescentLineSearchOptimizerv4.h.
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Counts the recursion depth for the golden section search
Definition at line 142 of file itkGradientDescentLineSearchOptimizerv4.h.
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Definition at line 132 of file itkGradientDescentLineSearchOptimizerv4.h.
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Controls the maximum recursion depth for the golden section search
Definition at line 139 of file itkGradientDescentLineSearchOptimizerv4.h.
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Definition at line 134 of file itkGradientDescentLineSearchOptimizerv4.h.
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Definition at line 135 of file itkGradientDescentLineSearchOptimizerv4.h.
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Definition at line 133 of file itkGradientDescentLineSearchOptimizerv4.h.